Read in data and get rid of first line

sea_ice_org <- read_csv("sea_ice.csv") %>% 
  clean_names() 
## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   Year = col_double(),
##   `#day` = col_double(),
##   Vol = col_double()
## )
sea_ice_org$date <- paste(sea_ice_org$year, sea_ice_org$number_day, sep = "_")

sea_ice_year <- sea_ice_org %>% 
  group_by(year)
sea_ice_dates <- read_csv("sea_ice_dates.csv") %>% 
  mutate(date = lubridate::mdy(standard_date),
         ice_volume = as.numeric(Vol)) %>% 
  as_tsibble(key = NULL, index = date) %>% 
  tsibble::fill_gaps()
## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   standard_date = col_character(),
##   new_date = col_character(),
##   Year = col_double(),
##   `#day` = col_double(),
##   Vol = col_double()
## )
sea_ice <- sea_ice_dates %>% 
  select(date, ice_volume)

Start to build an interactive something

sea_ice %>% 
  gg_season(year.labels=TRUE)+
  theme_dark() +
  scale_colour_gradient(low = "dodgerblue3", high="ivory")
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels
## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.
## Warning: Removed 10 row(s) containing missing values (geom_path).

ice_month <- sea_ice %>% 
  index_by(yr_mo = ~yearmonth(.)) %>% 
  summarize(monthly_mean_ice = mean(ice_volume, na.rm = TRUE))

ggplot(data = ice_month, aes(x = yr_mo, y = monthly_mean_ice)) +
  geom_line() 

# Or break it up by month: 
ice_month %>% 
  ggplot(aes(x = year(yr_mo), y = monthly_mean_ice)) +
  geom_line() +
  facet_wrap(~month(yr_mo, label = TRUE))

ice_annual <- sea_ice %>% 
  index_by(yearly = ~year(.)) %>% 
  summarize(annual_ice = mean(ice_volume, na.rm = TRUE))

ggplot(data = ice_annual, aes(x = yearly, y = annual_ice)) +
  geom_line()

sea_ice %>%
  ACF(ice_volume) %>%
  autoplot()

ice_month %>% 
  ACF(monthly_mean_ice) %>% 
  autoplot()

ice_dec <- ice_month %>% 
  model(STL(monthly_mean_ice ~ season(window = Inf)))

components(ice_dec) %>% autoplot()

sea_ice %>% 
  gg_season(year.labels=TRUE)+
  theme_minimal() 
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels
## Warning: Removed 10 row(s) containing missing values (geom_path).

dark_ice <- sea_ice %>% 
  gg_season(year.labels=TRUE, continuous=TRUE)+
  theme_dark() +
  scale_color_gradient(low="dodgerblue3", high="ivory") 
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels, continuous
## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.
dark_ice
## Warning: Removed 10 row(s) containing missing values (geom_path).

ggplot(data = ice_annual, aes(x = yearly, y = annual_ice)) +
  geom_line(color = "dodgerblue3", size = 1) +
  theme_minimal() +
  labs(x = "",
       y = "Artic Sea Ice Volume (km^3)")

gg_season(sea_ice, col = hsv(0.5, .35, seq(.45,.90,length.out = 15340))) +
  theme_minimal()+
  geom_line()
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Removed 10 row(s) containing missing values (geom_path).

## Warning: Removed 10 row(s) containing missing values (geom_path).

polar_season <- 
  gg_season(sea_ice, year.labels=FALSE, continuous=TRUE, polar = TRUE) +
  theme_void() 
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels, continuous
polar_season

arctic <- readJPEG("arctic.jpg")

polar_season_col <- 
  gg_season(sea_ice, year.labels=FALSE, continuous=TRUE, polar = TRUE, pal = pal_seegruen) +
  theme_void() +
  theme_void() 
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels, continuous
topo_yr <- ggdraw() +
  draw_image(arctic) +
  draw_plot(polar_season_col)
topo_yr

ggsave("topo_yr.png", width = 10, height =8)

rainbow_yr <- ggdraw() +
  draw_image(arctic) +
  draw_plot(polar_season)

rainbow_yr

polar_color <- 
  gg_season(sea_ice, year.labels=FALSE, continuous=TRUE, polar = TRUE) +
  theme_void() 
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels, continuous
polar_color

ggsave("polar_color.png", width = 8, height =8)

color_yr <- ggdraw() +
  draw_image(arctic) +
  draw_plot(polar_color)

color_yr

plot.new()
lim <- par()
rasterImage(arctic, lim$usr[1], lim$usr[3], lim$usr[2], lim$usr[4])

par(new=TRUE)
plot(polar_season)

ggsave("color_yr.png", width = 8, height = 8)

gg_season(sea_ice, col=topo.colors(15340), year.labels=TRUE)
## Plot variable not specified, automatically selected `y = ice_volume`
## Warning: Ignoring unknown parameters: year.labels
## Warning: Removed 10 row(s) containing missing values (geom_path).